• Title/Summary/Keyword: AI-based Platforms

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A Study of Power Line Communication-based Smart Outlet System Expandable at Home

  • Huh, Jun-Ho;Kim, Namjug;Seo, Kyungryong
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.901-909
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    • 2016
  • Unprecedented attention is being given to Smart Grid, Micro Grid and Internet of Things (IoT) in the Republic of Korea recently but such systems' effect is not well experienced by the market since they require additional and costly reforms for the existing household electrical system where adaptive communication platforms are needed. As such platforms, both wireless and wire communication technologies are being considered at the moment. Usually, they include WiFi, Zigbee technologies and the latter, LAN technology. However, communication speed decline due to signal attenuation and interference during wireless communications are considered to be the major problem and the extra works involving time and costs for the LAN system construction can be another demerit. Therefore, in this paper, we have introduced a Power Line Communication-based Smart Outlet System Expandable at Home to complement these disadvantages. Proposed IoT system involves Power Line Communication (PLC) technology which is essential to constructing a Smart Grid.

Learning Method of Data Bias employing MachineLearningforKids: Case of AI Baseball Umpire (머신러닝포키즈를 활용한 데이터 편향 인식 학습: AI야구심판 사례)

  • Kim, Hyo-eun
    • Journal of The Korean Association of Information Education
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    • v.26 no.4
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    • pp.273-284
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    • 2022
  • The goal of this paper is to propose the use of machine learning platforms in education to train learners to recognize data biases. Learners can cultivate the ability to recognize when learners deal with AI data and systems when they want to prevent damage caused by data bias. Specifically, this paper presents a method of data bias education using MachineLearningforKids, focusing on the case of AI baseball referee. Learners take the steps of selecting a specific topic, reviewing prior research, inputting biased/unbiased data on a machine learning platform, composing test data, comparing the results of machine learning, and present implications. Learners can learn that AI data bias should be minimized and the impact of data collection and selection on society. This learning method has the significance of promoting the ease of problem-based self-directed learning, the possibility of combining with coding education, and the combination of humanities and social topics with artificial intelligence literacy.

Cloud-IP based Broadcasting Media Production Technology (클라우드-IP 기반의 방송 미디어 제작 기술 동향)

  • H.J., Oh;J.Y., Lee;S.C., Kim;D.J., Choi
    • Electronics and Telecommunications Trends
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    • v.37 no.6
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    • pp.64-73
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    • 2022
  • This document describes the technologies related to internet protocol (IP)-based media production systems. As high-capacity, high-quality data transmission increases, broadcast production platforms are shifting to IP. The IP-based production system uses the network by sharing resources and is easy to control centrally. It also facilitates software-based cloud production. A cloud IP-based media production platform can work regardless of dedicated hardware and can easily collaborate. Associations and industrial groups have created common standards related to production, and manufacturers are developing solutions with their technologies based on their product competitiveness. This study investigates the open standard technologies used for IP-based media production and technology trends in the ProAV industry and describes the production in the cloud environment and cloud AI-based production technology trends.

A Research to realize a smart logistics warehouse system using 5G-based Logistics Automation Robot (5G 기반 물류 자동화 로봇을 활용한 스마트 물류 창고 시스템 구현을 위한 연구)

  • Park, Tae-uk;Yoon, Mahn-Suk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.532-534
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    • 2022
  • At a time when the 5G era is advancing beyond commercialization, places that used to handle simple logistics warehouse tasks are transforming into smart logistics warehouses by combining IT convergence technology and platforms. Smart logistics warehouses can accurately predict demand and inventory of products with AI, deep learning, and robot technologies based on 5G, and provide information on warehousing and warehousing status in real time. As the e-commerce market grows, the smart logistics sector is also growing rapidly. This paper implements a smart logistics warehouse system and studies and proposes a method of establishing a fast and accurate logistics system by utilizing 5G-based Logistics Automation Robot.

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Forecasting the Business Performance of Restaurants on Social Commerce

  • Supamit BOONTA;Kanjana HINTHAW
    • Journal of Distribution Science
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    • v.22 no.4
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    • pp.11-22
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    • 2024
  • Purpose: This research delves into the various factors that influence the performance of restaurant businesses on social commerce platforms in Bangkok, Thailand. The study considers both internal and external factors, including but not limited to business characteristics and location. Moreover, this research also analyzes the effects of employing multiple social commerce platforms on business efficiency and explores the underlying reasons for such effects. Research design, data, and methodology: Restaurants can be classified into different price ranges: low, medium, and high. To further investigate, we employed natural language processing AI to analyze online reviews and evaluate algorithm performance using machine learning techniques. We aimed to develop a model to gauge customer satisfaction with restaurants across different price categories effectively. Results: According to the research findings, several factors significantly impact restaurant groups in the low and mid-price ranges. Among these factors are population density and the number of seats at the restaurant. On the other hand, in the mid-and high-price ranges, the price levels of the food and drinks offered by the restaurant play a crucial role in determining customer satisfaction. Furthermore, the correlation between different social commerce platforms can significantly affect the business performance of high-price range restaurant groups. Finally, the level of online review sentiment has been found to influence customer decision-making across all restaurant types significantly. Conclusions: The study emphasizes that restaurants' characteristics based on their price level differ significantly, and social commerce platforms have the potential to affect one another. It is worth noting that the sentiment expressed in online reviews has a more significant impact on customer decision-making than any other factor, regardless of the type of restaurant in question.

A Model for Constructing Learner Data in AI-based Mathematical Digital Textbooks for Individual Customized Learning (개별 맞춤형 학습을 위한 인공지능(AI) 기반 수학 디지털교과서의 학습자 데이터 구축 모델)

  • Lee, Hwayoung
    • Education of Primary School Mathematics
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    • v.26 no.4
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    • pp.333-348
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    • 2023
  • Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.

A Case Study on Kakao's Resilience: Based on Five Levers of Resilience Theory

  • Song, Minzheong
    • International Journal of Internet, Broadcasting and Communication
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    • v.9 no.3
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    • pp.44-58
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    • 2017
  • The purpose of this study is to prove the Korean Internet company, Kakao's resilience capacity. For it, this paper reviews the previous literatures regarding Kakao's business models and discusses 'resilience' theory. Then, it organizes the research questions based on the theoretical background and explains the research methodology. It investigates the case of Kakao's business and organization. The case analysis shows that five levers of resilience are a good indicator for a successful platform business evolution. The five levers are composed of coordination, cooperation, clout, capability, and connection: First lever, coordination that makes the company to restructure its silo governance in order to respond to actual business flow starting from the basic asset like game and music content; second lever, cooperation where the firm provides creative people with playground for startups such as KakaoPage; third lever, clout where the company shares its data by opening its API of AI and chatbot to $3^{rd}$ party developers; fourth lever, capability where the firm establishes AI R&D center, KakaoBrain as the function of multi-domain generalist for developing diverse platforms tackling customer needs; and the last fifth lever, connection where the firm continues to expand its platform business to the peripheries, O2O businesses such as KakaoTaxi, KakaoOrder, KakaoPay, and KakaoBank. In conclusion, this study proposes Internet companies to be a resilient platform utilizing those five levers of resilience in order to form successful platform. This study contributes to the agile innovation of Internet platform with ecological sense.

A Study on Active Senior Travel Recognition Using ChatGPT (ChatGPT를 활용한 액티브 시니어 여행 인식 탐색 연구)

  • Han Jangheon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.3
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    • pp.25-35
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    • 2024
  • ChatGPT, a leading example of generative AI, is expanding the use of its LLM (Large Language Model) from traditional academic fields such as literature and creative writing to practical areas like management, tourism, and media. This study was conducted with active seniors to analyze their perceptions of travel and tourism, identifying key areas of interest and specific details. ChatGPT was utilized as an analytical tool in major areas of the study, providing suggestions for key findings.The research findings are as follows: First, terms closely associated with active senior travel include retirement, together, service, consumption, leisure, health, life, hobby, culture, generation, platform, wellness, and program. Second, centrality analysis showed that words like service, leisure, and together had high degrees of centrality and closeness centrality, while terms such as health, domestic, culture, activity, program, and life had high closeness centrality. Third, based on the CONCOR analysis with suggestions from ChatGPT, two clusters were identified: 'Retirement and Lifestyle' and 'Senior Services and Platforms'. Based on the research findings, practical implications for active senior travel were identified, along with academic implications for the field of tourism studies.

Automatic Generation of Video Metadata for the Super-personalized Recommendation of Media

  • Yong, Sung Jung;Park, Hyo Gyeong;You, Yeon Hwi;Moon, Il-Young
    • Journal of information and communication convergence engineering
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    • v.20 no.4
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    • pp.288-294
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    • 2022
  • The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

Metaverse and the Evolution of Food and Retail Industry

  • CHA, Seong-Soo
    • The Korean Journal of Food & Health Convergence
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    • v.8 no.2
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    • pp.1-6
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    • 2022
  • Purpose: This study aims to examine the opportunities in the food industry in the context of non-fungible tokens (NFTs) and the metaverse. The metaverse expands offline experiences into a virtual space and provides users with the advantage of overcoming the limitations of physical space. Research design, data and methodology: With the development of various contents based on advanced technology, the metaverse is becoming popular among the MZ generation (comprising millennials and Gen Zs), who are skilled at navigating digital platforms. Moreover, the previously entertainment game focused service has expanded to the business field after COVID-19; activities on the metaverse are now making space for economic value creation. I examined the recent global trends in the context of NFTs and the metaverse as well as the existing cases in Korea. Results: Globally, gaming and performance platforms such as Roblox, Fortnite etc. are still concentrated in the entertainment industry. However, as shown by ZEPETO and ifland in Korea there are many opportunities in the retail and food industries. Conclusions: We analyzed the ecosystems of the retail and food and beverage sectors, where the metaverse will be useful in the future, and have suggested the implications of the opportunities provided by the metaverse.